Statistical Molecular Design, Parallel Synthesis, and Biological Evaluation of a Library of Thrombin Inhibitors

Abstract

A library of thrombin inhibitors has been designed using statistical molecular design. An aromatic scaffold was used, with three varied positions corresponding to three pockets at the active site of thrombin (the S-, P-, and D-pockets). The selection was performed in the building block space, and previously acquired data were included in the design procedure. The design resulted in six, four, and six building blocks for the first (S), second (P), and third (D) pockets, respectively. A second round of selection applied to the combined selected building blocks resulted in a subset of 18 compounds. The selected library was synthesized in parallel and biologically evaluated. The compounds were analyzed with respect to their inhibition (pIC(50)) of thrombin; membrane permeability, estimated by migration behavior in micellar media (CE log k') and pK(a); and specificity with respect to inhibition (K(i)) of trypsin. Multivariate QSAR studies of the responses yielded valuable results and information that could only be found using statistical molecular design in combination with multivariate analysis.

Fragment‐based Lead Discovery and Optimization Using X‐Ray Crystallography, Computational Chemistry, and High‐throughput Organic Synthesis

“…In principle, the best optimization approach from a statistical experimental design perspective [56][57][58] would be to construct combinatorial libraries based on the original fragment hit by simultaneously varying substituents at each of its synthetic "handles". This approach would reveal both additive and non-additive substituent effects.…”

Selectivity of Neutral/Weakly Basic P1 Group Inhibitors of Thrombin and Trypsin by a Molecular Dynamics Study

“…[7] However, finding an inhibitor that comprises both selectivity and suitable pharmacokinetics A C H T U N G T R E N N U N G has been difficult to identify, prompting research to A C H T U N G T R E N N U N G continue. [8][9][10][11] The selectivity of small-molecule inhibitors toward a protein or enzyme target is often of crucial importance in the development of therapeutically useful molecules. Engineering high selectivity can be especially challenging when the site of interaction between the inhibitor and enzyme is Abstract: Molecular dynamics (MD) simulations followed by molecular mechanics generalized Born surface area (MM-GBSA) analyses have been carried out to study the selectivity of two neutral and weakly basic P1 group inhibitors (177 and CDA) to thrombin and trypsin.…”

“…A schematic representation of the active site is shown in Figure 1. [8] The specificity pocket consists of a hydrophobic "channel" with the carboxylic acid of Asp189 [17] and two backbone carbonyl groups in the bottom of the pocket. The former forms strong ionic interactions with amine-, guanidine-, or amidine-type structures located at the terminus of a hydrophobic spacer.…”

Controlling coverage of D‐optimal onion designs and selections

“…A fast and optimal approximation to this search is to base it on a small but representative subset of the whole set of compounds. One approach for this purpose is statistical molecular design (SMD) [1][2][3]. The initial step in SMD is to quantitatively and multivariately describe the candidate compounds.…”

“…An alternative approach would be to use algorithmic selection engines such as D-optimal design (DD) [8] or space-filling (SF) design. For example, Linusson et al [2] used DDs to select a library of thrombin inhibitors. However, DD also has its shortcomings, such as the tendency to select only the most extreme compounds on the periphery of the design space.…”